Borealis Dataverse OAI Archive
metadata only
CC BY-NC-ND 4.0
Additional data for: Machine-learning–enabled virtual screening delivers scaffold-diverse, experimentally validated, c-MET inhibitors
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- AI-Enhanced Adaptive Virtual Screening Platform Enabling Exploration of 69 Billion Molecules Discovers Structurally Validated FSP1 Inhibitors#10055
- An Observatory for the MET Oncogene: A Guide for Targeted Therapies#1146490
- Automated synthetic cell-based screening for designed proteins with emergent functions.#461509
- Integration of computational and experimental techniques for the discovery of PLpro covalent inhibitors. When large virtual screening and rational design meet#129330
- Boltzina: Efficient and Accurate Virtual Screening via Docking-Guided Binding Prediction with Boltz-2#1049662
Record · ID 204974
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive